Quality by design and Process analytical technology, It leads to current trends in Pharmaceutical Analysis, and based on ICH Q8, Q9 and Q10 guidelines

1. CURRENT TRENDS IN
PHARMACEUTICAL ANALYSIS
:QBD & PAT
1
Sunil N Patil
Research Associate
Ipca Lab, Mumbai

2. OUTLINE
 Introduction to QbD & PAT
 Pharmaceutical Development –ICH Q8(R2).
 Role of Analytical Methods in QbD Process.
 QbD analytical method development strategies.
 PAT
 Optimization by PAT
 Case study
 Conclusion
2

3. INTRODUCTION TO QUALITY BY DESIGN(QBD)
 QbD is defined as “a Systematic approach to
pharmaceutical development and manufacturing that
begins with predefined objectives & emphasizes product &
process understanding & process control, based on sound
science & quality risk management”
 Quality by Design (QbD) is a concept first outlined by J.M.
Juran.
 Quality cannot be tested into products – it has to be built by
design.
 Quality by Testing and Inspection QbD
3

4. OVERVIEW OF QbD

5. PHARMACEUTICAL DEVELOPMENT – ICH
Q8(R2)
 The aim is to design a quality product and its manufacturing
process to consistently deliver the intended performance of the
product.
 Describes science and risk-based approaches for
pharmaceutical product and manufacturing process
development.
 Introduced concepts of design space and flexible regulatory
approaches.
 Introduced concepts of Quality by Design (QbD).
5

6. 6
ICH Q8
Pharmaceutical
Development
ICH Q10
Pharmaceutical
Quality System
ICH Q9
Quality Risk
Management
Quality by
Design

7. Intended Use
Route of administration
Patient population
…..
Product Design
Intended Use
Route of administration
Patient population
…..
Product Design
Design Specifications
(Customer requirements)
Manufacturing Process
Goals
•High degree of process
understanding
•To ensure a low risk of
releasing a poor quality product
•High efficiency through
continuous learning and
improvement

8. 09/25/2014
8
Elements of Pharmaceutical Development- ICH Q8 (R2)

9. ROLE OF ANALYTICAL METHODS IN QBD MFG.
PROCESS
Raw
Material
Testing
• Specification based on product QTPP and CQAs.
eg. Particle size, crystal properties etc.
In process
Testing
• Real time (at-, on-, or in-line) measurements,
Process Analytical Technology (PAT):
eg. NIR- identification, drying, blending, assay,
and content uniformity.
• Active control of process to minimize product
variation.
Stability
Testing
• Predictive models at release minimize stability
failures.
9

10. THE CONCEPT OF ATP (ANALYTICAL TARGET
PROFILE)
 PhRMA and EFPIA working group introduced an
approach that describes predefined performance
requirements of analytical methods. i.e. ATP.
 ATP: Defines what the method has to measure (e.g.
the level of a specified impurity) & to what level the
measurement is required (i.e. performance level
characteristics).
 ATP measures requirements defined in CQAs of Drug
products. 10

11. QBD ANALYTICAL METHOD
DEVELOPMENT STRATEGIES
Define
Method Goal
Method
Scouting &
Evaluation
Method
Selection &
Risk
Assessment
Method
Performance
Control
Strategy
Method
Validation
11
Figure. Generalized method development strategy (MDS) approach for QbD
analytical methods.

12. DEFINE METHOD GOAL
• eg. The goal of an HPLC method for API- To
separate & Quantify the main compound &
impurities (CQAs) that may impact the quality
of the drug product.
Define Method
requirements:
i.e. ATP.
• eg. For chromatographic resolution for 2
adjacent peaks must not be less than 1.5
Define the
Method
Attributes:
• eg. Temperature, Humidity, etc.
Operational
intent of
Method: 12

13. METHOD SCOUTING AND EVALUATION
 Systematic Design of Experiments (DoEs) approach:
eg. RP-HPLC: Systematic & automatic Screening of
all three key components (Column, pH & organic
modifier ), then optimization of chromatographic
performance by using simulation softwares.
 Optimization predicts large number of method
conditions based on limited data from screening
experiments.
13

14. METHOD SELECTION & RISK ASSESSMENT
Method selection: It is desirable to select at least
one backup method.
Risk Assessment: It involves the risk identification
& prioritization of risk in structured fashion, followed
by ruggedness & robustness testing.
Tools used: Fishbone diagram, FMEA (Failure
Mode Effect Analysis), MSA (Measurement System
Analysis).
14

15. FMEA (FAILURE MODE EFFECT ANALYSIS )
 It evaluates potential failure modes for method & their
likely effect on method performance.
 FMEA methodically breaks down the Analytical method
into process steps & identify possible failure modes for
each step.
 Each failure mode is ranked on estimated frequency of
 occurrence (O),
 probability ,
 process (D) &
 severity(S).
 Failure risks is calculated by Risk Priority Numbers
(RPNs)= O × D × S 15

16. FMEA FOR A PAT NIR METHOD USED FOR DRYING MONITORING
Step Failure mode Failure effects Sev. Occ. Det. RPNs
Probe control Interlock with
Agitator
Probe cannot be
inserted
7 4 4 112
Probe damage
, Fiber damage
No signal
transmission or
Data gathering
Loss of data & control
on drying
10 4 4 160
Retraction
performance
Probe fails in
insertion position
Agitator cannot be
started
10 4 4 160
PLS model PLS model for NIR
needs updating
Error in prediction of %
w/w water content
10 1 7 70
Software NIR Software
Failure
Loss of data & control
on drying
4 1 1 4
16

17. MEASUREMENT SYSTEM ANALYSIS (MSA)
 MSA is used in the design and analysis studies to
determine the reproducibility of the method.
 MSA is used to identify the noise factors which
will have to be controlled & factors that do not
have impact on method performance under
normal operating conditions.
eg. for typical HPLC method the risk assessment
is performed for Noise factors such as Different
Analyst, column batches, laboratories, sample
batches & date of analysis.
17

18. METHOD DESIGN SPACE
 Method Design Space (MDS): Multidimensional
space formed by the factor ranges that is used
during method development which assures quality
data (robustness).
 In contrast to the ATP, the MDS is related to a
specific method.
 MDS is also known as Method Operable Design
Region (MODR).
18

19. METHOD PERFORMANCE CONTROL
STRATEGY
 Method control strategy: Controls analytical
factors and parameters and ensures that analytical
method performance criteria are met.
 It assures that method will be performed as
intended on a routine use.
 System suitability Test (SST):
eg. Resolution value between critical pair of
peaks, acceptable value for tailing peaks etc. 19

20. QBD LIFECYCLE APPROACH FOR ANALYTICAL METHOD
20
Figure 1: Components of application of quality by design (QbD) to analytical methods .

21. COMPARISON BETWEEN TRADITIONAL & QBD
APPROACH
Method Development
by OFAT (one-factor-
at-a-time)
Method Transfer
Method Developed
independently by
Transferring lab.
Then several batches are
selected & run by both
transferring & receiving labs
prior to completing method
transfer
Traditional
Approach
Method Development by using DoEs
Approach.
Systematic Screening & Optimization
Approach.
Method Transfer
Risk assessment is performed in
Receiving laboratory, so that any
risk can be located prior to the
method transfer.
QbD
Approach
21

22. PAT (Process Analytical Technologies)
• A scientific and risk based approach to acquire process
understanding.
• An important enabler for QbD.
• A paradigm most easily applied to new products.
What is PAT not?
• PAT is not a one-size-fits-all solution.
• Difficult to fully implement for legacy products.

23. Process Analytical Technology (PAT)
PAT includes:
• Timely measurements during processing
• Critical quality and performance attributes
• Raw and in-process materials
• At-line, on-line or in-line measurements founded on “Process
Understanding”
• Opportunities for improvement.
• More reliable and consistent processes (& product)
• Less failures, less reworks, less recalls
• Flexibility w.r.t. scale and equipment
• Better / faster Quality Systems.
• Process Enhancement Opportunities

24. PAT is not just Analytical and not
only NIR…...!!
• Raman
• Image/Vision
• Acoustics
• Fluorescence
• UV/Vis
• FBRM (Laser scattering)
• LIBS
• etc……….
In conjunction with….
• Process Engineering
• SPA (Data Acquisition)
• Multivariate Data Analysis
Summary - Tools in the toolbox

25. Desired situation:
Variable raw material parameters + Variable manufacturing process =
Fixed output

26. Difference between PAT and QbD
• PAT and QbD share similar goals for pharmaceutical
manufacturing
a. Process understanding
b. Process control
c. Risk based decisions
•PAT facilitates the implementation of QbD
• Some elements of QbD (e.g., dosage form selection,
formulation development, design space) can be implemented
without PAT

27. A QBD BASED METHOD DEVELOPMENT FOR THE
DETERMINATION OF IMPURITIES IN A PEROXIDE
DEGRADED SAMPLE OF ZIPRASIDONE
• 1:UPLC method development by
using QbD approach for
determination of impurities in a
peroxide degraded sample of
Ziprasidone
• 2:Subsequent Method transfer to
HPLC.
Objectives
27
CASE STUDY

28. 1: QBD APPROACH TO UPLC METHOD DEVELOPMENT
 A QbD approach to method development uses statistical
Design of Experiments (DoE) to develop a robust method
‘Design Space’.
 Fusion AE method development software in conjugation
with Empower 2 used to facilitate a more comprehensive
QbD approach to method development.
 Screening (PHASE-1)
28
Flow
rate
Inj.Vol. Column
Temp.
Gradient
Time
Variables
0.6
mL/mi
n
2 µl 30 ºc 5 min Stat. & mob. Phase,
gradient % organic, mobile
phase pH 2.5-10.5
Table: Initial screening parameters.

29. Initial Screening Results
 Using variable parameters, an Experimental Design was
generated within Fusion AE
 Partial factorial Design selected by software to obtain max. amt.
of information with least No. of experimental run.
29
Parameters Description of parameters
Column ACQUITY UPLC CHS C18
2.1× 50 mm, 1.7 µm
Mobile Phase D1: Water with 0.1% Formic acid
(pH 2.5)
Gradient % organic 87.5 % Water/Acetonitrile
Table2: Initial Screening results of variable parameters.

30. Optimization (PHASE-2)
30
Parameters Description of Parameters
Column ACQUITY UPLC C18,
2.1 × 50 mm, 1.7 µm
Mobile Phase A: Acetonitrile ,
D1: Water with 0.1% Formic acid (pH 2.5)
Gradient endpoint 87.5 % Acetonitrile
Variables Gradient time, Column temp.
Inj. Volume, flow rate
Data management Empower 2 CDS, Fusion AE
Table: Optimization of variable parameters.

31. Final Optimization Results.
 Secondary effectors Such as Column temp, inj. Volume,
Gradient time & flow rate varied.
 A new experimental Design generated by Fusion AE.
 After processing data in Fusion AE, the final optimized
method was generated.
31
Parameters Description of parameters
Column ACQUITY UPLC CHS C18
2.1× 50 mm, 1.7 µm
Mobile Phase D1: Water with 0.1% Formic
acid (pH 2.5)
Gradient % organic 0-87.5 % Water/Acetonitrile
Gradient time 8.1 min
Column temp. 30ºc
flow rate 0.8 mL/min
Table: Final optimization results.

32. 32
Fig.Initial method from screening expt for ziprasidone peroxide degradation.
Fig . Final optimized method for ziprasidone peroxide degradation showing
improved peak tailing and resolution.

33. DESIGN SPACE FOR UPLC METHOD
DEVELOPMENT
33
Figure . The design space region showing the independent effects of gradient time and pump
flow rate on method success.
•Multi-dimensional plots in Fusion AE facilitates visualization
of the effect of each factor on separation

34. METHOD TRANSFER
34
•The UPLC method developed using Fusion AE software was transferred to
HPLC to demonstrate transferability from a method development laboratory to
other laboratory that might not be equipped with UPLC.
Figure. Method transfer from UPLC to HPLC for ziprasidone peroxide
degradation.

35.  A robust method for ziprasidone was developed in two days
using a QbD approach on an ACQUITY UPLC H-Class
system running Empower 2 and Fusion AE Method
Development software.
 It allows for rapid screening and optimization across a wide
range of column chemistries, mobile phases and pH ranges,
while evaluating the effects of secondary factors such as
column temperature, flow rate, injection volume and gradient
time on the separation.
 The UPLC method developed for ziprasidone was transferred
to HPLC in one step using a Method Transfer Kit and
ACQUITY UPLC Columns Calculator.
35

37. PROCESS ANALYTICAL TECHNOLOGY
Analytical in the context of PAT includes much more than
measuring, it is all about an overall process understanding!

38. 38
CONCLUSIONS
 Method developed with QbD approach are more robust &
rugged, and thus survive the challenges of long-term usage by
QC laboratories with decreased likelihood of failure.
 Design Space (DS) for Analytical Methods provides possibility
to move inside the DS without need for post–approval changes
in process.
 Method transfer by QbD approach are more successful without
need for revalidation for any Out of specification results.

39. 39
International Conference on Harmonization Tripartite Guideline “Q8(R2):
Pharmaceutical Development” August 2009.
International Conference on Harmonization Tripartite Guideline “Q9: Quality
Risk Management” November 2005.
International Conference on Harmonization Tripartite Guideline “Q10:
Pharmaceutical Quality System” June 2008.
F.G. Vogt, A.S. Kord, REVIEW Development of Quality-By-Design Analytical
Methods, J. Pharm. Sci. 100 (2010) 797-812.
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